Both economic and environmental modelling require observations on the systems they simulate in order to be parameterized, calibrated and evaluated. Environmental modelling is then used to assess consequences of the behavioural changes on air, water, soil, climate change or biodiversity (Schulp et al., 2008, Verboom et al., 2007). Policy impact assessment of the CAP and other legislation affecting agriculture such as the Water or Nitrate directives typically involves economic modelling to evaluate how agents react to the incentives and disincentives emerging from proposed legislation. Now, it deals additionally with a far more complex bundle of targets including interalia food safety, animal health, water and air quality, soil fertility, contribution to the livelihood of rural communities or maintenance of High Nature Value farmland. The early CAP mainly targeted productivity increases to ensure food security and encompassed instruments to sustain farming income. A good example of this is the Common Agricultural Policy (CAP) of the European Union. In high per capita income countries where the vast majority of the population has access to food, housing, health care and basic education the focus of policy has slowly shifted towards the fulfilment of needs that were previously not considered pressing. There is growing consensus that impact assessment of societal choices needs to account for social, economic and environmental consequences and their tradeoffs (European Union, 2001, Foley et al., 2005, Rindfuss et al., 2004). The findings of this study contribute to our overall capacity to integrate approaches from different disciplines in the integrated analysis of land change and the ex ante assessment of environmental and economic effects of agricultural policies. Therefore, relative changes in land use classes at 1 km × 1 km resolution obtained from CLUE simulations update a priori means in CAPRI-Spat entering a Highest Posterior Density Estimator. It concludes that a stronger integration of the geographic and economic aspects can be achieved by linking the overall land use dynamics simulated by CLUE to the detailed representation of the agricultural sector by CAPRI-Spat. This paper discusses differences between the two models relating to geographical units, distribution algorithm and most importantly diverging interpretation of ‘agricultural land’, in relationship to their respective concepts and objectives. The mapping units are clusters of 1 km × 1 km pixels considered homogenous in terms of soil, slope, land cover and administrative region. Whereas, CAPRI-Spat is concerned with agricultural land use, disaggregating cropping shares, animal stocking densities, yield and agricultural input use for mapping units. CLUE focuses on disaggregating national level changes in claims for agricultural and urban area to a 1 km × 1 km grid, explicitly addressing consequences of changing demands for agricultural and urban area for other land uses such as (semi-) natural vegetation. It does so by comparing two existing approaches (CLUE and Capri-Spat) for the European Union (EU27). This paper explores how interactions between economic and geographic aspects of the land system can be strengthened in modelling studies. Different studies represent the interactions between the economic and geographic components of the land system in different ways. These results are primarily downscaled from the national or regional scale to a spatial resolution appropriate for environmental impact analysis. Recent European research projects have developed approaches that downscale land use related results of economic models.
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